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  • Presentation: 2019-11-27 13:15 Gamma, Västerås
    Khanfar, Husni
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Demand-Driven Static Backward Program Slicing Based on Predicated Code Block Graphs2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Static backward program slicing is a technique to compute the set of program statements, predicates and inputs that might affect the value of a particular variable at a program location. The importance of this technique comes from being an essential part of many critical areas such as program maintenance, testing, verification, debugging, among others. The state-of-art slicing approach collects all the data- and control-flow information in the source code before the slicing, but not all the collected information are used for computing the slice. Thus, this approach causes a significant amount of unnecessary computations, particularly for slicing large industrial systems, where unnecessary computations lead to wastage of a considerable amount of processing time and memory. Moreover, this approach often suffers from scalability issues.

    The demand-driven slicing approaches aim at solving this problem by avoiding unnecessary computations. However, some of these approaches trade precision for performance, whereas others are not entirely demand-driven, particularly for addressing unstructured programs, pointer analysis, or inter-procedural cases.

    This thesis presents a new demand-driven slicing approach that addresses well-structured, unstructured, and inter-procedural programs. This approach has four distinct features, each of which prevents a special type of unnececessary computations. The effectiveness and correctness of the proposed approach are verified using experimental evaluation. In addition, the thesis proposes an approach that can compute on the fly the control dependencies in unstructured programs.

  • Presentation: 2019-12-16 09:15 Beta, Västerås
    Daraei, Mahsa
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Production planning of CHP plants integrated with bioethanol production and local renewables2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Production planning of an energy system is dependent on parameters such as energy demand and energy conversion technologies, which are influential in making decisions on operation strategy and optimal performance of the system. In accordance with the European Union energy policy, the share of renewable resources in the energy supply is growing. Improvement in energy technology is considered to be a pathway to achieve the target of 100% renewable power supply in Sweden by 2040. Increased utilization of renewable resources in energy systems and transportation sectors as well as improved energy conversion technologies would add complexity to the systems. Development of such complex systems depends on several key parameters, including availability of local resources, changes in daily energy use behavior, market price and weather conditions. Therefore, optimization and long-term production planning of such systems will be crucial considering the alternating nature of renewable resources.  

    The aim of this thesis is to develop an optimization model for a regional energy system to provide advanced knowledge for production planning for combined heat and power (CHP) plants. The energy system in the county of Västmanland in central Sweden is used as the case for study. The regional system consists of CHP plants, heat only boilers and renewable resources. Two different optimization cases are developed for the analysis, one with increased energy supply from local renewables, and the other with integrated transport fuels production in a polygeneration system. The model includes the whole chain from availability of resources to the final energy use. 

    The effect of different parameters relating to trends in energy demand and supply on operational strategy of the studied system is investigated by developing different scenarios. The potential solar power production from grid-connected solar cells installed on the rooftops of buildings in the region is added to the system in the base scenario. Then, the first scenario analyzes the increased application of heat pumps to replace the district heating in some of the buildings in the region. The influence of electrification of the transportation system as a result of increased penetration of electric vehicles is investigated in the second scenario. Two further scenarios evaluate the effects of integration of bioethanol production with existing CHP plants and increased application of bioethanol cars and hybrid vehicles in the regional transportation system. 

    The study demonstrates the importance of production planning of the energy system at the regional scale in relation to resource availability and energy imports. The main conclusion of this thesis is that the polygeneration and increased use of heat pumps could influence the production planning of the system in terms of fuel use, plants operation, fossil-based emissions, and energy demand and import. However, increased use of hybrid vehicles represents the optimal case for the mentioned parameters.

    The full text will be freely available from 2019-11-25 08:00
  • Presentation: 2019-12-17 09:15 U2-024, Västerås
    Trinh, Lan Anh
    Mälardalen University, School of Innovation, Design and Engineering.
    Dependable Path Planning for Autonomous Control2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Changing from automatic to autonomous control has emerged as the main shift on the development of robots nowadays. The autonomous control allows robot to have more freedom as well as direct interactions with human and other robots. Having a dependable platform for autonomous control becomes crucial when building such a system. The dependability of a robotic agent is presented by main attributes including availability, i.e. the continuous operations of the system over a time interval, reliability, i.e. the ability of the system to provide correct services, and safety, i.e. the robotic agent must ensure safe controls to avoid any catastrophic consequences on users, other robots, and finally the environment. Considering path planning is one of the key components of an autonomous control system for robotic agents, the works presented in this thesis aim at building a dependable, i.e. safe, reliable and effective, path planning algorithm for a group of robots that share their working space with humans. Firstly, the method for path planning of multiple robotic agents is proposed based on a novel dipole flow field idea.The any angle-path planning with Theta* algorithm is employed to initialise the paths from a starting point to a goal for a set of agents. To deal with static obstacles while a robot is going on the way to its goal, a static flow field along the configured path is defined. A dipole field is then calculated to avoid the collision of agents with the other agents and human subjects. In this approach, each robotic agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent, with a strength proportional the velocity. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. Meanwhile, the fault analysis of multiple robots with Petri net is demonstrated to understand the cooperation of multiple robotic agents to solve the shared tasks. Thereafter, the Petri net is applied together with the path planning to address the collision avoidance by synchronising the movement of robots through a cross. Continuously, the multiple path planning has investigated to support fault tolerance for the path planning algorithm. This is to deal with the deadlock situation where the agent takes very long time to reach the goal or even is not able to do so. The agent is equipped with different paths to the goal and proactively switch among the plans whenever needed to avoid the deadlock. Finally, the whole framework has been implemented by a widely used platform, robot operating system (ROS), and evaluated through Gazebo simulator.

  • Presentation: 2019-12-17 13:15 Paros, Västerås
    Danielsson, Jakob
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Characterization of Shared Resource Contention in Multi-core Systems2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Multi-core computers are infamous for being hard to use in time-critical systems due to execution-time variations as an effect of shared resource contention. In this thesis we study the problem of shared resource contention which occurs when multiple applications executing on different cores do not have exclusive ownership of a shared resource. We investigate performance variations of parallel tasks in multi-core systems and present a method to pinpoint the source of the resource contention using existing hardware performance counters. Furthermore, we investigate methods to mitigate performance variations using resource isolation techniques. We present a methodology for verifying isolation and tested the achieved isolation using the Jailhouse hypervisor. We further investigate shared cache memory isolation techniques using a page coloring tool called PALLOC. Page-coloring is used for partitioning the cache, assigning specific cache lines to specific processes. Page coloring can however cause system performance degradation since it decreases the total amount of cache memory available for each process. Finally, we propose a dynamic partitioning assignment policy which assigns cache partitions to a process according to an adaptive model based on the process performance. The general conclusion from our investigations is that a large body of applications can suffer from shared resource contention and that techniques for mitigating resource contention are in dire need. Our methods measure and characterise applications, identifies resource contention and finally study isolation techniques.  

  • Presentation: 2019-12-18 09:15 Kappa, Västerås
    Tsog, Nandinbaatar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Improving On-Board Data Processing using CPU-GPU Heterogeneous Architectures for Real-Time Systems2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis investigates the efficacy of heterogeneous computing architectures in real-time systems.The goals of the thesis are twofold. First, to investigate various characteristics of the Heterogeneous System Architectures (HSA) compliant reference platforms focusing on computing performance and power consumption. The investigation is focused on the new technologies that could boost on-board data processing systems in satellites and spacecraft. Second, to enhance the usage of the heterogeneous processing units by introducing a technique for static allocation of parallel segments of tasks.

    The investigation and experimental evaluation show that our method of GPU allocation for the parallel segments of tasks is more energy efficient compared to any other studied allocation. The investigation is conducted under different types of environments, such as process-level isolated environment, different software stacks, including kernels, and various task set scenarios. The evaluation results indicate that a balanced use of heterogeneous processing units (CPU and GPU) could improve schedulability of task sets up to 90% with the proposed allocation technique.